Application and follow-up data have now been collected from fifteen different Village. Capital programs. These data ...
What’s Working in Startup Acceleration Insights from Fifteen Village Capital Programs EXECUTIVE SUMMARY
VillageCapital SOCIALENTERPRISEGOIZUETA
Acknowledgements Authors
Peter W. Roberts, Academic Director Social Enterprise @ Goizueta, Emory University Saurabh Lall, Research Director Aspen Network of Development Entrepreneurs Ross Baird, Executive Director Village Capital Emily Eastman, Program Associate Social Enterprise @ Goizueta, Emory University Abigayle Davidson, Research Analyst Aspen Network of Development Entrepreneurs Amanda Jacobson, Latin America Manager Village Capital
This report would not have been possible without support from the leadership and staff at Village Capital. In addition to Ross and Amanda, we would like to single out contributions by Victoria Fram, Brittney Riley, Dustin Shay, Nasir Qadree, George Omedo, Kristen Moree, Varun Pawar, Allyson Plosko and Whitney Muse. We would also like to thank the Village Capital entrepreneurs, mentors and other program stakeholders who took the time for our interviews. Your insights and contributions to this report are greatly appreciated. We also recognize that the Global Accelerator Learning Initiative (GALI) has been made possible by its co-creators and founding sponsors, including the U.S. Global Development Lab at the U.S. Agency for International Development, Omidyar Network, The Lemelson Foundation and the Argidius Foundation. Additional support for GALI has been provided by the Kauffman Foundation and Stichting DOEN.
Introduction Public and private sector organizations are showing increasing interest in supporting small and growing businesses (SGBs) as catalysts for broad-based economic development. This is stimulating a range of support mechanisms for early-stage entrepreneurs, including incubators, angel investor networks, training programs and more recently, accelerator programs. Accelerators, which emerged in 2005 with the launch of Y-Combinator, have some distinct characteristics:
`` They tend to be limited in duration; `` They work with cohorts of early-stage entrepreneurs; and `` They aim to facilitate connections with potential investors. Despite the emergence of hundreds of accelerator programs around the world, we know little about their effectiveness or how differences across programs influence venture performance. To address this gap, Social Enterprise @ Goizueta at Emory University and the Aspen Network of Development Entrepreneurs (ANDE) launched the Global Accelerator Learning Initiative (GALI) in collaboration with a consortium of public and private funders. GALI builds on the Entrepreneurship Database Program at Emory University, which works with accelerator programs around the world to collect and analyze data describing the entrepreneurs that they attract and support. Village Capital – a seed-stage accelerator that runs programs for entrepreneurs in impactoriented sectors – was the first to work with the Entrepreneurship Database Program, starting in 2013. Application and follow-up data have now been collected from fifteen different Village Capital programs. These data provide a unique opportunity to examine the performance of ventures accelerated by these different Village Capital programs compared to those that applied but were not selected.
I N S I G H T S F R O M F I F T E E N V I L L AG E C A P I TA L P R O G R A M S
2
The Early Impacts of Acceleration: Honing in on Program Performance Contrasts
This report examines the effects of Village Capital accelerators on three measures of entrepreneurial performance: `` Revenues; `` Full-time employment; and `` Investment. We started by comparing performance changes of the ventures that participated in these fifteen programs to the change in performance of ventures that applied but were rejected:
FIFTEEN VILLAGE CAPITAL PROGRAMS REJECTED ENTREPRENEURS AVERAGE
1-Year Revenue Growth
$7,934
1-Year Employee Growth
0.95 employees
PARTICIPATING ENTREPRENEURS AVERAGE
$11,329
table 01
STATISTICALLY SIGNIFICANT DIFFERENCE?*
No
1.36 employees
No
$6,274
$54,236
Yes
Equity
$2,570
$24,588
Yes
Debt
$2,357
$16,410
Yes
Philanthropy
$1,347
$13,238
Yes
1-Year Investment Growth
Sample Size
427
138
N/A
* At the p < 0.05 level
3
W H AT ’ S WO R K I N G I N S TA R T U P AC C E L E R AT I O N
On average and across the board, participating and rejected entrepreneurs improved performance in the year after applying to a program. However, the growth figures for participating entrepreneurs are consistently higher than those of the rejected entrepreneurs. Most importantly, while the average rejected entrepreneur increased new investment by $6,274, the average participating entrepreneur grew investment by $54,236. While these comparisons suggest that participating entrepreneurs tend to outperform rejected entrepreneurs, our goal is to dig deeper and learn from differences across the fifteen programs. Thus, we identified the “highest-performing” and “lowest-performing” Village Capital programs based on the three metrics:
HIGHEST-PERFORMING PROGRAMS
1-YEAR REVENUE GROWTH DIFFERENCE
1-YEAR EMPLOYEE GROWTH DIFFERENCE
table 02
1-YEAR INVESTMENT GROWTH DIFFERENCE
APPLICATION YEAR
COUNTRY TYPE*
TECHFOCUSED
Agriculture & Cleantech: Louisville
2013
Developed
Some what
$73,882
1.09
$84,528
FinTech Mexico
2014
Developing
Yes
$108,777
1.42
$21,398
Energy: Boulder & Houston (US)
2014
Developed
No
$18,109
0.81
$141,888
EdTech: DC & Chicago (US)
2014
Developed
Yes
$114,667
3.28
$97,478
PROGRAM
LOWEST-PERFORMING PROGRAMS
APPLICATION YEAR
COUNTRY TYPE*
TECHFOCUSED
1-YEAR REVENUE GROWTH DIFFERENCE
Impact: Nairobi
2013
Developing
No
$21,812
-0.46
$10,941
Health IT: Houston & Salt Lake City (US)
2014
Developed
Yes
-$343,658
-2.88
$55,689
Kenya: Innovations for Agriculture
2014
Developing
Yes
-$169,249
0.30
$23,128
Last Mile: Ahmedabad
2014
Developing
No
-$4,700
-2.27
$21,626
PROGRAM
1-YEAR EMPLOYEE GROWTH DIFFERENCE
table 03
1-YEAR INVESTMENT GROWTH DIFFERENCE
* Based on the World Bank’s country classification. Countries designated as High-Income (with per capita GNI > $12,736) are classified as “Developed”, with all others classified as “Developing”.
I N S I G H T S F R O M F I F T E E N V I L L AG E C A P I TA L P R O G R A M S
4
To better understand these program performance contrasts, we assembled a panel of Village Capital program experts and asked them to brainstorm all of the possible reasons for the differences. We consolidated their 133 reasons into a concise typology and then focused on seven predictions that were raised most often by the program experts: 1. Partner quality improves program performance. 2. Time spent on program-related activities lowers program performance. 3. Quality of the applicant pool improves program performance. 4. More advanced ventures benefit more from acceleration. 5. Networking among cohort members improves program performance. 6. Emphasis on financial acumen improves program performance. 7. Mentor quality improves program performance. Using a combination of quantitative and qualitative research strategies, we dug deeper into each of these predictions, relying on our detailed entrepreneur application data, additional surveys of accelerator program managers, and structured interviews with key program stakeholders.
5
W H AT ’ S WO R K I N G I N S TA R T U P AC C E L E R AT I O N
Key Findings Partner quality improves program performance
SUPPORTED
Partner organizations were rated much higher in the high-performing programs. Relative to those that worked on the low-performing programs, these organizations were described as “engaged”; “putting entrepreneurs first”; and “contributing to program content.” We asked three senior Village Capital leaders – each with broad experience across the fifteen programs – to “give a quick and simple grade to each partner”; with a grade of 1 indicating below average partner performance; 2 indicating average or expected partner performance; and 3 indicating above-average partner performance. These ratings were based on a “holistic assessment of the quality of contributions to program effectiveness.” Partner grades, which were averaged across the three Village Capital leaders, were much higher for the ten partners that worked on high-performing programs; an average grade of 2.52, compared to just 1.76 for the nine partners who worked on the low-performing programs.
Time spent on program-related activities lowers program SUPPORTED performance
Rather than spending as much time as possible delivering program content, high-performing programs tended to set aside more time for entrepreneurs to work on their own. We asked program managers to “give us a rough idea of how a typical entrepreneur allocated his/her time”, allowing us to tell how much time was spent working on site versus remotely, and how much time was spent working with other entrepreneurs, with mentors, or on their own. According to program managers, the percentage of time spent working with other entrepreneurs and/or mentors (versus working on their own) was 53% for the high-performing programs and 83% for low-performing programs.
More advanced ventures benefit more from acceleration NOT SUPPORTED
Program selectors for the high-performing programs placed more emphasis on the quality or promise of the underlying idea than on the venture itself. This led them to select ventures that were younger on average (1.73 years), compared to ventures in low-performing programs (2.47 years).
I N S I G H T S F R O M F I F T E E N V I L L AG E C A P I TA L P R O G R A M S
6
Quality of the applicant pool improves program SUPPORTED performance
The high-performing programs had smaller applicant pools on average. However, their applicants tended to have more intellectual property and more educational, entrepreneurial and senior management experiences:
APPLICANT POOL CHARACTERISTICS
AVERAGE FOR HIGH- PERFORMING PROGRAMS
AVERAGE FOR LOW- PERFORMING PROGRAMS
table 04
STATISTICALLY SIGNIFICANT DIFFERENCE? *
Total number of applicants
75.6
98.5
—
Percentage with patents
27.5%
21.9%
Yes
Percentage with copyrights
20.5%
14.0%
Yes
Percentage with trademarks
39.7%
27.0%
Yes
Percentage of teams with college degrees
56.2%
39.0%
Yes
Percentage of teams with prior For-Profit founding experience
68.9%
57.1%
Yes
Percentage of teams with prior Nonprofit founding experience
25.8%
27.0%
No
Percentage of teams with CEO / ED experience
46.0%
31.4%
Yes
* At the p < 0.05 level
Networking among cohort members improves program LIMITED SUPPORT performance
Descriptions of cohort dynamics were mainly positive in both high and low-performing programs. While the differences were modest, participants in high-performing programs described the cohorts as being more partnership-oriented and as having more peer-to-peer involvement. Participants in low-performing programs did not describe a lack of peer-to-peer involvement in their cohorts but emphasized individual qualities, such as creativity and innovation.
7
W H AT ’ S WO R K I N G I N S TA R T U P AC C E L E R AT I O N
Emphasis on financial acumen improves program performance NOT SUPPORTED
The high-performing programs spent less time working on finance, accounting, and formal business plan development and more time on presentation and communication skills, networking, and organization structure and design.
PERCENT OF EMPHASIS PLACED ON DIFFERENT PROGRAM TOPICS
figure 01
■ High-Performing Program Average ■ Low-Performing Program Average
24%
20% 18%
18%
15%
10%
14% 11%
9%
8% 5%
4%
Accounting
11%
Business Plan Development
Finance
Human Relations
8% 5%
9%
8%
5%
Legal
Marketing
Networking
Mentor quality improves program performance
Organization Presentation & Structure & Communication Design Skills
MIXED SUPPORT
High-performing programs connected entrepreneurs with a larger number of mentors. However, this did not translate into more time spent with mentors overall. While all programs tended to use similar individuals as mentors, there is some evidence that program alumni are not very effective mentors and that including potential customers as mentors is a good idea.
8
Implications for Village Capital (Response by Ross Baird)
These findings provide several insights for individuals looking to develop more effective accelerator programs: `` Accelerators have better results with ventures that have some initial revenues, but need to “speed up” investment; `` We need program partners who will roll up their sleeves; `` For the applicant pool, focus on quality not quantity; `` ‘Less is more’ when it comes to program content; `` Programs need to focus more on building entrepreneurial networks, and less on delivering content; `` While understanding financials is clearly necessary for investment readiness, we should not be building more content or classes around finance and accounting; and `` If you’re an entrepreneur, don’t take accelerators at their word when they say “we provide mentorship”—ask who those mentors are and what they will be doing.
9
W H AT ’ S WO R K I N G I N S TA R T U P AC C E L E R AT I O N
Invitation to Join GALI This is the first report among many that will use our expanding dataset to examine specific cause-effect relationships that lie behind effective accelerator program decision-making. In this spirit, we invite interested accelerators to consider joining the Entrepreneurship Database Program to begin developing a more comprehensive understanding of acceleration practices and impacts. Although our accelerator partners are asked to devote time and energy to this project, they also gain from participation by getting:
`` Deeper insights from reports about applicant pools, selection biases and impacts
on revenue, employment and investment growth based on all entrepreneurs who apply to your program. These reports are valuable for programs that want to demonstrate impacts to program funders and supporters; and
`` Visibility from the broader GALI network, which provides benefits for those looking
to develop more visible platforms for participating entrepreneurs.
We invite you to indicate your interest by answering a few questions at: http://goo.gl/forms/pHTYHLVeHq.
GALI works in association with the Global Entrepreneurship Research Network; a working coalition of institutions funding research as a tool in realizing the full potential of entrepreneurship to create inclusive prosperity on a global scale.
ANDE is a policy program of The Aspen Institute. Photos generously provided by: 9 John-Michael Maas/Darby Communications / Cover, 2, 3, 6, 7, 8, 10, Back Cover Village Capital
The views expressed in this document reflect the personal opinions of the authors and are entirely the authors’ own. They do not necessarily reflect the opinions of the U.S. Agency for International Development (USAID) or the United States Government. USAID is not responsible for the accuracy of any information supplied herein.
SOCIALENTERPRISEGOIZUETA
Emory’s Entrepreneurship Database Program Visit us online at www.entrepreneurdata.com Contact us at
[email protected]
ANDE Research Initiative Visit us online at www.andeglobal.org/research_initiative Contact us at
[email protected]
TO V IE W T HE F ULL REPOR T, PLE A SE V ISI T A NDEGLOB A L .ORG /ACCELER ATOR S .